Search Results for "data" - Page 48
Sort By:
Showing 3125 open source projects for "data"
View related business solutions-
Cut Cloud Costs with Google Compute EngineSave on compute costs with Compute Engine. Reduce your batch jobs and workload bill 60-91% with Spot VMs. Compute Engine's committed use offers customers up to 70% savings through sustained use discounts. Plus, you get one free e2-micro VM monthly and $300 credit to start.
-
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
-
1
dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
2
BitcoinExchangeFH
Cryptocurrency exchange market data feed handler
BitcoinExchangeFH is a slim application to record the price depth and trades in various exchanges. You can set it up quickly and record all the exchange data in a few minutes! If the exchange is not supported with the WebSocket API feed, it will automatically fall into using its REST API feed. The subscription section specifies the exchange and instruments to subscribe. After receiving the order book or trade update, each handler is updated. For example, for SQL database handler, it is updated with the corresponding SQl statements. ... -
3
Python 3 Network Packet Sniffer
A Network Packet Sniffing tool developed in Python 3
A Network Packet Sniffer developed in Python 3. Packets are disassembled as they arrive at a given network interface controller and their information is displayed on the screen. This application depends exclusively on the NETProtocols library (also developed and maintained by EONRaider) from version 2.0.0 and above and can be run by any Python 3.8+ interpreter. -
4
Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. ... -
$300 in Free Credit for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credit—no hidden charges. Test, build, and deploy without risk. Use your credit across the Google Cloud platform to find what works best for your needs. After your credits are used, continue building with free monthly usage products. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
CapitalGainsCalc
Converts simple lists of lots and sales into a TXF file
US Tax Forms (1040 Schedule D and 8949 supplemental forms) require that every capital gains sale is listed by line, even if no cost basis or even a 1099-B has been provided to the IRS. Entering this data into tax software like TurboTax is tedious and error prone. Some institutions provide limited export capabilities such as CSV or excel export but this is not easy to translate into tax preparation software. These python scripts convert two simple to generate input files BuyLots.csv and Sales.csv into a .TXF file that can be imported into tax prep software and a second RemainingLots.csv that can be used for next year. ... -
6
SASA Tool
SWATH-Auto System Analyzer Tool, SASA Tool
SWATH-Auto System Analyzer Tool, SASA Tool, is a novel SWATH platform for non-targeted metabolomics data analysis with an accurate mass spectral library for metabolite identification using SWATH acquisition mode. -
7
WaveRNN
WaveRNN Vocoder + TTS
...The repository includes scripts and code for preprocessing datasets such as LJSpeech, training Tacotron to produce mel spectrograms, training WaveRNN on those spectrograms (with optional GTA data), and finally generating audio. A quick_start.py script allows users to immediately synthesize example sentences from a pretrained model and inspect both generated audio and attention plots. For custom TTS, the project guides you through training Tacotron, forcing GTA spectrogram export when desired, training WaveRNN with or without GTA, and then running joint generation. -
8
Brain Tokyo Workshop
Experiments and code from Google Brain’s Tokyo research workshop
...Each project explores innovative approaches to learning, prediction, and creativity in neural networks, often through unconventional or biologically inspired methods. The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems. -
9
DomE
Implements a reference architecture for creating information systems
...The architecture comprises elements that guarantee user access through automatically generated interfaces for various devices, integration with external information sources, data and operations security, automatic generation of analytical information, and automatic control of business processes. All these features are generated from the domain model, which is, in turn, continuously evolved from interactions with the user or autonomously by the system itself. Thus, an alternative to the traditional software production processes is proposed, which involves several stages and different actors, sometimes demanding a lot of time and money without obtaining the expected result. ... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
-
10
Whisper Library
Whisper is a file-based time-series database format for Graphite
Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data. Copies data from src in dst, if missing. Unlike whisper-merge, don't overwrite data that's already present in the target file, but instead, only add the missing data (e.g. where the gaps in the target file are). ... -
11
Blankly
Easily build, backtest and deploy your algo in just a few lines
Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable... -
12
LaTeX Cookbook
A comprehensive LaTeX template with examples for theses, books, etc.
This repo contains a LaTeX document, usable as a cookbook (different "recipes" to achieve various things in LaTeX) as well as a template. The resulting PDF covers LaTeX-specific topics and instructions on compiling the LaTeX source. -
13
QuickPlot
Simple user interface for gnuplot aimed for reflectometry data
Graphical user interface for gnuplot to create publication quality figure very quickly. It supports templates for fast formatting of graphics, different plot styles, insets, axis and label options. One important feature is storing metadata in png and pdf files that can be used to reload any graph saved with QuickPlot. -
14
L5RCM
GM tool for the RPG game "Legend of the Five Rings" 4th edition
This is a GM tool for the RPG game "Legend of the Five Rings" 4th edition. It can be used to create PC and NPC and to manage characters during playtime. The Legend of the Five Rings RPG is a role playing game that takes place in Rokugan, a mixture of Asian medieval culture. You can find more on L5R RPG on its official site. -
15
m2cgen
Transform ML models into a native code
...Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase in their native Python libraries. Currently, m2cgen works only with float64 (double) data type. You can try to cast your input data to another type manually and check results again. Also, some small differences can happen due to specific implementation of floating-point arithmetic in a target language. -
16
TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid. -
17
Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make... -
18
ELECHEM & FARADAY (Electrochemical)
Simulation tool for electrochemical / electroplating parameters
FARADAY and ELECHEM are the two portable computer programs, find useful for electrochemical researchers, electroplating units, battery as well as supercapacitor industries, process engineers, materials scientists & engineers, electroplaters, hobbyists, and students to evaluate various electrochemical deposition parameters. These computational tools can be used to simulate various electrochemical deposition data or electroplating parameters for metals, alloys, composites as well as energy efficiency of the process. For more information, visit to project Home page: https://www.enote.page/2022/07/computer-simulation-electrochemical.html Designed by: Dr. M Kanagasabapathy, Asst. Professor Department of Chemistry Rajapalayam Rajus’ College Affiliated to Madurai Kamaraj University Rajapalayam, (TN) INDIA 626117 https://rrc.ac.in/images/faculty_info/2%20MKS.pdf -
19
MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the... -
20
PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
21
AugLy
A data augmentations library for audio, image, text, and video
...AugLy is a great library to utilize for augmenting your data in model training, or to evaluate the robustness gaps of your model! We designed AugLy to include many specific data augmentations that users perform in real life on internet platforms like Facebook's -- for example making an image into a meme, overlaying text/emojis on images/videos, reposting a screenshot from social media. While AugLy contains more generic data augmentations as well, it will be particularly useful to you if you're working on a problem like copy detection, hate speech detection, etc. -
22
Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
...Texar-PyTorch integrates many of the best features of TensorFlow into PyTorch, delivering highly usable and customizable modules superior to PyTorch native ones. Texar-PyTorch (this repo) and Texar-TF have mostly the same interfaces. Both further combine the best design of TF and PyTorch. Data processing, model architectures, loss functions, training and inference algorithms, evaluation, etc. -
23
LayoutParser
A Unified Toolkit for Deep Learning Based Document Image Analysis
With the help of state-of-the-art deep learning models, Layout Parser enables extracting complicated document structures using only several lines of code. This method is also more robust and generalizable as no sophisticated rules are involved in this process. A complete instruction for installing the main Layout Parser library and auxiliary components. Learn how to load DL Layout models and use them for layout detection. The full list of layout models currently available in Layout Parser.... -
24
Haircut_MF
Fetches the historical Haircut data (%) of Mutual Funds and Bonds
...It is based on previous closing price (NAV). This program is used to identify the real value of an equity / share / mutual fund / Bonds / SGB with date. This program fetches the historical Haircut data (%) of Mutual Funds / bonds listed in NSE at a selected date. Enter the Date (in the format: dd-mm-yyyy) to get Haircut data for equities listed in NSE. It lists the haircut data (%) against the mutual funds on the given date. At the same time .csv file consists of NSE symbol of the equity, previous closing price and haircut value (%) will be downloaded with a filename of the given date. ... -
25
Ungoogled Chromium Android
Android build for ungoogled-chromium
...The goal is to offer an Android browser that feels familiar in capability and rendering fidelity but does not phone home, engage with proprietary APIs, or leak usage data to third-party providers. Because Android’s ecosystem is heavily tied to Google’s app services, this effort focuses on ensuring core browsing functionality, tab management, extension support (as available), and performance optimizations.
